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Record W2790260643 · doi:10.4095/306557

The Ontario Geological Survey's groundwater initiative: deliverables, data, derivatives and future direction

2018· report· en· W2790260643 on OpenAlexaboutno aff
R P M Mulligan, Andy F. Bajc, F R Brunton, A K Burt, K M Dell, S M Hamilton, E H Priebe

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDeliverableGroundwaterGeological surveyGeologyEnvironmental planningEnvironmental scienceEngineeringSystems engineeringGeophysicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Regional mapping investigations by the Ontario Geological Survey (OGS) to support groundwater studies in southern Ontario have expanded significantly since 2001. The OGS groundwater initiative involves the collection and dissemination of high-quality geoscience data to enhance characterization of the subsurface through the execution of three mapping activities; 3-D Paleozoic bedrock mapping, 3-D Quaternary sediment mapping, and ambient groundwater geochemistry mapping. 3-D Paleozoic bedrock mapping studies aim to characterize and delineate stratigraphic units that host aquifers and control local and regional bedrock groundwater flow systems. Mapping, drilling and collaborative investigations in Silurian strata along the Niagara Escarpment (including 397 boreholes) have led to an improved understanding of the occurrence, connectivity and genesis of karst systems as well as the hydraulic properties of these bedrock flow systems (GRS16). Integrative studies have also supported the mapping of groundwater recharge areas and chemical evolution profiles (MRD337) for key hydrostratigraphic units. The next phase of study involves mapping bedrock units, buried cuestas and bedrock potable groundwater flow zones in upper Silurian to Middle Devonian strata of southwestern Ontario. 3-D Quaternary sediment mapping investigations produce 3-D models of regional-scale stratigraphic units. The models aid in hydrostratigraphic assessment and correlation of sediment units as well as the delineation of potential recharge areas and a better understanding of surface water-groundwater interactions. Projects are complete in Waterloo (GRS03), Brantford-Woodstock (GRS10), Barrie-Oro (GRS11), and Orangeville-Fergus (GRS15). Borehole data collected for the South Simcoe area is available (MRD324) and model construction is nearing completion. Geophysical data collected by the Geological Survey of Canada to support ongoing mapping in the Niagara (MRD353) and south and central Simcoe areas are available (GSC OF8251; 7883; 8252). Results from 3-D sediment mapping projects have produced a database of subsurface information from >350 boreholes in southern Ontario. The ambient groundwater geochemistry project provides an improved understanding of the relationships between groundwater chemistry and the composition of aquifers in southern Ontario, as well as insights on the flow evolution, residence time, and vulnerability of groundwater systems, through the collection and analysis of untreated bedrock- and overburden-derived groundwater at >1850 locations (MRD283-REV). Ambient geochemistry data have led to the identification of multiple natural and anthropogenic factors locally affecting groundwater quality in the province. Derivative products include improved characterization and delineation of rapid recharge areas and subsurface karst terrain. Ongoing work has shifted focus to Ontario's near-north, from Manitoulin Island eastward to the North Bay area. In the future, the groundwater initiative aims to enhance integration of its three core activities thereby providing a holistic approach to assessments of the provincial groundwater resource. Continued investigations will allow for the synthesis of information from individual regional studies to scales suitable for the analysis across multiple watersheds and possibly at the scale of the Great Lakes drainage basin.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.104
GPT teacher head0.272
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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